Explores text mining of long-tail data in neuroscience and brain connectivity, including named entity recognition, protein concentration mining, and comparison of connectivity matrices.
Covers the implementation of an information system for managing taxi trajectories, including filtering data, creating trajectory models, and comparing performance.
Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.
Offers a comprehensive introduction to Data Science, covering Python, Numpy, Pandas, Matplotlib, and Scikit-learn, with a focus on practical exercises and collaborative work.
Explores data handling fundamentals, including models, sources, and wrangling, emphasizing the importance of understanding and addressing data problems.
Covers the heterogeneous neuroscience data, techniques like microarrays and gene sequencing, data integration, and the importance of metadata in organizing and sharing data.
Explores the concept of Knowledge Graphs and their role in data integration and semantic understanding, showcasing real-world examples and applications.
